A study of effects due to Laplace pressure and thermal Marangoni convection for micro-droplet driving with three dimensional numerical simulation.

2016 ◽  
Vol 2016 (0) ◽  
pp. 0701
Author(s):  
Nobuo KAZUNO ◽  
Takahiro TSUKAHARA ◽  
Masahiro MOTOSUKE
Keyword(s):  
Numerical Simulation ◽  
Marangoni Convection ◽  
Three Dimensional ◽  
Laplace Pressure

scholarly journals Optimal Control of SiC Crystal Growth in the RF-TSSG System Using Reinforcement Learning

Crystals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 791
Author(s):  
Lei Wang ◽  
Atsushi Sekimoto ◽  
Yuto Takehara ◽  
Yasunori Okano ◽  
Toru Ujihara ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Growth Rate ◽  
Reinforcement Learning ◽  
Marangoni Convection ◽  
Three Dimensional ◽  
Development Cost ◽  
Rf Coil ◽  
Melt Flow ◽  
2D Numerical Simulation ◽  
Top Seeded Solution Growth

We have developed a reinforcement learning (RL) model to control the melt flow in the radio frequency (RF) top-seeded solution growth (TSSG) process for growing more uniform SiC crystals with a higher growth rate. In the study, the electromagnetic field (EM) strength is controlled by the RL model to weaken the influence of Marangoni convection. The RL model is trained through a two-dimensional (2D) numerical simulation of the TSSG process. As a result, the growth rate under the control of the RL model is improved significantly. The optimized RF-coil parameters based on the control strategy for the 2D melt flow are used in a three-dimensional (3D) numerical simulation for model validation, which predicts a higher and more uniform growth rate. It is shown that the present RL model can significantly reduce the development cost and offers a useful means of finding the optimal RF-coil parameters.

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